Mechanism-of-Action Classification of Antibiotics by Global Transcriptome Profiling

Abstract

Antimicrobial resistance (AMR) is an ever-growing public health problem worldwide. The low rate of antibiotic discovery coupled with the rapid spread of drug-resistant bacterial pathogens is causing a global health crisis. To facilitate the drug discovery processes, we present a large-scale study of reference antibiotic challenge bacterial transcriptome profiles, which included 37 antibiotics across 6 mechanisms of actions (MOAs) and provide an economical approach to aid in antimicrobial dereplication in the discovery process. We demonstrate that classical MOAs can be sorted based upon the magnitude of gene expression profiles despite some overlap in the secondary effects of antibiotic exposures across MOAs. Additionally, using gene subsets, we were able to subdivide broad MOA classes into subMOAs. Furthermore, we provide a biomarker gene set that can be used to classify most antimicrobial challenges according to their canonical MOA. We also demonstrate the ability of this rapid MOA diagnostic tool to predict and classify the expression profiles of pure compounds and crude extracts to their expression profile-associated MOA class.

Silver Nanoparticles Induce a Triclosan-Like Antibacterial Action Mechanism in Multi-Drug Resistant Klebsiella pneumoniae

“…We hypothesized that the bactericidal activity of L-Ag NPs could be due to a hitherto unknown mechanism, rather than the most commonly reported oxidative stress based bactericidal activity ( Durán et al, 2016 ). To investigate, we compared our RNA-seq data to the transcriptional response of E. coli exposed to 37 antimicrobial compounds ( O’Rourke et al, 2020 ). This global transcriptional profile of E. coli exposed to 37 antibiotics generated a list of 447 genes whose signature expression pattern characterized the mechanism of action associated with each antibiotic, leading the authors to hypothesize that the antibacterial action mechanism of any unknown/uncharacterized compounds can be deduced by comparing the transcriptional profile of a compound of interest with that of these 447 E. coli MG1665 K12 genes.…”

Early Drug Development and Evaluation of Putative Antitubercular Compounds in the -Omics Era

“…So an alternative route to identify potential drug targets is through transcriptomic data obtained either through microarrays or RNA-Seq ( Fields et al, 2017 ). O’Rourke et al (2020) investigated transcriptomic profiles of 37 antibiotics within six different mechanisms of action, which allowed blind predictions of the antibiotic class based on transcriptomic response with an accuracy of <80%. A similar model was developed for M. marinum ( Boot et al, 2018 ).…”

A How-To Guide for Mode of Action Analysis of Antimicrobial Peptides

“…While genomic approaches map the level of antibiotic sensitivity, transcriptomic and proteomic approaches map the stress response profiles of bacteria to antibiotic stress, which are diagnostic for the individual compound's mechanism of action and can aid target identification (Bandow et al, 2003;Bandow and Hecker, 2007;Wenzel and Bandow, 2011). While microarrays have been the predominant technique for transcriptomic profiling for a long time, RNA sequencing is now the method of choice in most cases, since it is more sensitive, does not rely on hybridization probes, and is becoming more and more affordable (Hutter et al, 2004b;Gilad et al, 2009;O'Rourke et al, 2020). Many studies have successfully used transcriptomic profiling to aid mode of action analysis (Briffotaux et al, 2019;O'Rourke et al, 2020) and its uses have been extensively reviewed elsewhere (Freiberg et al, 2004;Wecke and Mascher, 2011).…”

“…While microarrays have been the predominant technique for transcriptomic profiling for a long time, RNA sequencing is now the method of choice in most cases, since it is more sensitive, does not rely on hybridization probes, and is becoming more and more affordable (Hutter et al, 2004b;Gilad et al, 2009;O'Rourke et al, 2020). Many studies have successfully used transcriptomic profiling to aid mode of action analysis (Briffotaux et al, 2019;O'Rourke et al, 2020) and its uses have been extensively reviewed elsewhere (Freiberg et al, 2004;Wecke and Mascher, 2011). However, it should be noted that parameters for stress response profiling, be it transcriptomic or proteomic experiments, must be chosen with care.…”

“…Metabolomics is a comparatively young -omics technique that has not been extensively employed for mechanistic antibiotic studies yet. In contrast to genomics, transcriptomics, and proteomics (Bandow et al, 2003;Tamae et al, 2008;Liu et al, 2010;O'Rourke et al, 2020), there are no large comparative metabolomic studies on antibiotic stress yet. However, bacterial metabolomics has been employed for a variety of applications including identification of new antibiotics and characterizing resistance mechanisms (Gao and Xu, 2015;Wu et al, 2015;Li et al, 2019) and is emerging as a tool in mode of action studies (Wang et al, 2019;Liu et al, 2020).…”